svishwa/crowdcount-cascaded-mtl

Single Image Crowd Counting (CNN-based Cascaded Multi-task Learning of High-level Prior and Density Estimation for Crowd Counting)

crowdcount-cascaded-mtl's Issues

run test.py error

cuda runtime error!
When trying to run test.py I get the following message:
(pytorch) zhouyao@wb-i36g:~/crowdcount-cascaded-mtl$ python test.py --gpu 0
Pre-loading the data. This may take a while...
Loaded 100 / 182
Completed laoding 182 files
/home/zhouyao/anaconda3/envs/pytorch/lib/python2.7/site-packages/h5py/init.py:36: FutureWarning: Conversion of the second argumen t of issubdtype from float to np.floating is deprecated. In future, it will be treated as np.float64 == np.dtype(float).type.
from ._conv import register_converters as _register_converters
/home/zhouyao/crowdcount-cascaded-mtl/src/crowd_count.py:25: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.
density_cls_prob = F.softmax(density_cls_score)
THCudaCheck FAIL file=/opt/conda/conda-bld/pytorch_1513363039688/work/torch/lib/THC/generic/THCTensorCopy.c line=70 error=77 : an ill egal memory access was encountered
Traceback (most recent call last):
File "test.py", line 45, in
density_map = density_map.data.cpu().numpy()
File "/home/zhouyao/anaconda3/envs/pytorch/lib/python2.7/site-packages/torch/tensor.py", line 35, in cpu
return self.type(getattr(torch, self.class.name))
File "/home/zhouyao/anaconda3/envs/pytorch/lib/python2.7/site-packages/torch/cuda/init.py", line 370, in type
return super(_CudaBase, self).type(*args, **kwargs)
File "/home/zhouyao/anaconda3/envs/pytorch/lib/python2.7/site-packages/torch/_utils.py", line 38, in type
return new_type(self.size()).copy(self, async)
RuntimeError: cuda runtime error (77) : an illegal memory access was encountered at /opt/conda/conda-bld/pytorch_1513363039688/work/t orch/lib/THC/generic/THCTensorCopy.c:70

Any suggestions for what might be wrong.

How to output the crowd count ?

Hello, when I run test.py I get the grayscale density maps, however I don't find the crowd count like it is outputted in your paper. How do we get it ?

Model download issue

I met a issue when i tried to access to the DropBox. So i would be appreciated that if you can provide the final train model in Baidu disk.

Thank you.

为什么要灰度化

您好！请问为什么得到的结果都是灰度图像，而paper中的是彩色图像，是训练需要吗？

A question for training

Hello,I ran the code you provided, but I was unable to reproduce the effect of the paper,I can only lower my MAE to 30. I have a question if there are any training technique?

Error running test.py

When trying to run test.py I get the following message:
File "test.py", line 4, in
from src.crowd_count import CrowdCounter
File "ROOT/crowdcount-cascaded-mtl/src/crowd_count.py", line 5, in
import network
ModuleNotFoundError: No module named 'network'

Thanks in advance for your help

UC_FF_50 processing code

Dear svishwa, I am not getting shanghatitech images publicly. I also emailed to the authors but yet I dint get any kind of links of the dataset. I have UCF dataset. Can you please provide me the UC_FF_50 data processing marlab codes, if available?

count group classification labels

How to make the ‘count group classification labels’ mentioned in the paper？Thank you！

how to test on new images

I have crowd images gathered by a security camera. I have all jpg files. How do I run your code on only jpg files. From what I have seen your code requires '.mat'+'.jpg' files in order to produce output. But in my case I donot have .mat file

Any pointers will really help

usage Models

How to use trained model for other crowd dataset images.

could you please convert the matlib code to python code?

evaluate count do not effective in this network.

epoch: 0, step 525, Time: 0.0011s, gt_cnt: 0.0, et_cnt: 7.1
epoch: 0, step 530, Time: 0.0011s, gt_cnt: 59.5, et_cnt: 6.9
epoch: 0, step 535, Time: 0.0010s, gt_cnt: 0.0, et_cnt: 7.4
epoch: 0, step 540, Time: 0.0010s, gt_cnt: 1.0, et_cnt: 7.2
epoch: 0, step 545, Time: 0.0010s, gt_cnt: 0.0, et_cnt: 6.7
epoch: 0, step 550, Time: 0.0010s, gt_cnt: 2.0, et_cnt: 6.4
epoch: 0, step 555, Time: 0.0010s, gt_cnt: 3.0, et_cnt: 6.0
epoch: 0, step 560, Time: 0.0010s, gt_cnt: 0.0, et_cnt: 6.2
epoch: 0, step 565, Time: 0.0010s, gt_cnt: 3.1, et_cnt: 6.3
epoch: 0, step 570, Time: 0.0010s, gt_cnt: 1.0, et_cnt: 6.0
epoch: 0, step 575, Time: 0.0010s, gt_cnt: 7.6, et_cnt: 5.6
epoch: 0, step 580, Time: 0.0010s, gt_cnt: 0.0, et_cnt: 5.8

It seems like that the evaluate count is continuous,but not appeared in 'mcnn' network. What's more, the density maps draw a blank.

Hi,what is the label tool do you use?

Issues

Hi, I didn't download the Pre-trained model files [Shanghai Tech A], [Shanghai Tech A],Can you seed me the files to the email, My email is [email protected]. Thank you very much

Softmax runtime warning

UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.
this is the original code line: density_cls_prob = F.softmax(density_cls_score)
So how do I know whether dim should be taken '0' or '1'

dataset download issue

Hi I am getting

for the dropbox link and

for the Baidu link when trying to download the shanghaitech tech ds.
I was wondering if I can download them elsewhere, for example, are these the same as the ones here:
https://www.kaggle.com/datasets/tthien/shanghaitech
which can be used directly or have you guys modified?

how to fix the invalid value problem

when i change my own dataset , it comes out with:
D:\project\mtl\src\utils.py:8: RuntimeWarning: invalid value encountered in true_divide
density_map = 255*density_map/np.max(density_map)

Dataset

Hi,
Could you please share the link to ShanghaiTech dataset?
Thank you in advance.

the output image is grayscale

when I run test.py, I found the output image is grayscale while it should be colorful in your paper, what should I do to solve this question.

et_cnt 显示为0